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Ai Math Trainer Jobs in Arizona (NOW HIRING)

DataAnnotation

Economist - AI Trainer

Phoenix, AZ · On-site +1

$40/hr

AI models are increasingly capable of performing complex analytical and scientific reasoning -- but ... A bachelor's degree in a quantitative field is preferred (Statistics, Computer Science, Mathematics ...

DataAnnotation

Physicist - AI Trainer

Phoenix, AZ · On-site +1

$40/hr

AI models are increasingly capable of performing complex analytical and scientific reasoning -- but ... A bachelor's degree in a quantitative field is preferred (Statistics, Computer Science, Mathematics ...

DataAnnotation

Economic Analyst - AI Trainer

Phoenix, AZ · On-site +1

$40/hr

AI models are increasingly capable of performing complex analytical and scientific reasoning -- but ... A bachelor's degree in a quantitative field is preferred (Statistics, Computer Science, Mathematics ...

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Ai Math Trainer information

What is an AI Math Trainer job?

An AI Math Trainer is responsible for developing, curating, and refining mathematical problems and solutions to train AI models. They ensure that AI systems understand and generate accurate mathematical reasoning by reviewing datasets, annotating problems, and validating AI-generated responses. This role requires strong math skills, attention to detail, and the ability to work with AI development teams. AI Math Trainers help improve AI's ability to handle mathematical concepts across various difficulty levels.

What are the key skills and qualifications needed to thrive in the Ai Math Trainer position, and why are they important?

To thrive as an AI Math Trainer, you need a strong background in mathematics, machine learning, and data analysis, usually supported by a degree in mathematics, computer science, or a related field. Familiarity with AI development frameworks (such as TensorFlow or PyTorch), scripting languages (like Python), and experience with data labeling or annotation platforms is highly valuable. Excellent communication, attention to detail, and problem-solving abilities are important soft skills for this role. These skills ensure that complex mathematical concepts are accurately translated and effectively used to train AI models, leading to high-quality, reliable AI systems.

What are some typical daily responsibilities of an AI Math Trainer?

As an AI Math Trainer, your typical day involves curating and creating high-quality mathematical content, annotating datasets, and designing training materials to enhance the performance of mathematical AI models. You may collaborate closely with data scientists, AI engineers, and product teams to identify gaps in AI understanding and tailor your training resources accordingly. Reviewing model outputs for accuracy and providing detailed feedback are also important aspects of the role. This position offers a dynamic work environment that blends technical expertise with educational oversight, allowing you to directly impact the development and improvement of advanced AI solutions.
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Ai Math Trainer jobs near you
Industrial Engineer - AI Trainer

Industrial Engineer - AI Trainer

DataAnnotation

Phoenix, AZ • On-site, Remote

$60/hr

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

Join the DataAnnotation team and contribute to developing cutting‐edge AI systems, while enjoying the flexibility of remote work and setting your own schedule. We are looking for experienced quantitative professionals to help advance AI development. AI models are increasingly capable of performing complex analytical and scientific reasoning — but these systems still need practitioners with real‐world quantitative experience to validate whether the outputs actually hold up in practice.

That's where you come in. As a member of DataAnnotation's team, you'll work closely with state‐of‐the‐art AI models on tasks like evaluating AI‐generated quantitative analysis, solving technical problems, and providing feedback that directly shapes how these systems reason about data, models, and scientific problems. Whether your background is in data science, astrophysics, economics, biostatistics, operations research, or any other quantitative field, if you think rigorously about data and models, your skills are directly applicable here.

Some team members fit this work alongside a full‐time role, while others treat it as their primary focus. To get started, once you sign up for an account, you'll take a short assessment (this serves as our version of an interview). If you pass, you'll receive an email confirmation, and paid work will become available on our platform.

Benefits Fully remote: work from anywhere in the US, Canada, UK, Ireland, Australia, and New Zealand. Flexible schedule: choose which projects you take on and when you work. Competitive pay: projects are paid hourly, up to $60 USD/hour.

Impact: help shape the future of AI systems built to reason about data and analytics. Responsibilities Evaluate AI‐generated quantitative work, including statistical analysis, predictive modeling, scientific reasoning, and data‐driven insights, for technical accuracy and real‐world validity. Design and solve quantitative problems used to train and benchmark AI systems, spanning areas like forecasting, experimental analysis, optimization, and statistical inference.

Write clear technical explanations and well‐documented analytical code. Provide feedback that directly shapes the next generation of AI models built for quantitative reasoning. Qualifications 2+ years of hands‐on experience in a quantitative role or research environment — such as data science, statistics, economics, finance, physics, biology, epidemiology, operations research, or any adjacent field.

Some coding experience required, with comfort writing and reviewing analytical code end‐to‐end. Practical experience with statistical methods, predictive modeling, and experiment design (e.g., A/B testing, hypothesis testing, regression, classification, time‐series forecasting). Fluency in English (native or bilingual level) with strong writing skills.

A bachelor's degree in a quantitative field is preferred (Statistics, Computer Science, Mathematics, Engineering, or similar); a master's or PhD is a plus. Relevant credentials are a plus (e.g., Kaggle Competition ranking, AWS/GCP ML certifications, or equivalent demonstrated expertise). Payment is made via PayPal.

We will never ask for any money from you. This job is only available to those in the US, Canada, UK, Ireland, Australia, and New Zealand. #J-18808-Ljbffr

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